Limited resources but countless problems and proposed solutions - policy-making is complex. The evidence is rarely clear-cut, preferences diverge and biases further skew our vision.
Where do we start? What matters most? Questions that can feel impossible to answer. And yet, not replying to them also gives an answer: let chance decide.
Unless we tackle the hard questions, future generations will look back at us and just see dart-throwing chimps.
Multi-criteria decision analysis (MCDA) makes stakeholder relationships more structured and transparent.
MCDA guides the collective exploration of a problem and the co-creation of possible solutions. It provides psychological comfort while highlighting knowledge gaps and laying the necessary groundwork for policy learning.
MCDA is useful in collective decision-making due to its capacity to account for multidimensional problems, quantitative and qualitative data, competing interests and differing judgments. Its vast applications have proven its adaptability and employability across cultures and domains to make better choices and systematically learn from them.
Our training programs are currently being tested with a selected audience.
Target audience: Teams, groups and networks of policy actors
Project lead: Maxime Stauffer
Duration of the exercise: 2 hours
Political decision-making, the process by which actors blend information, resources and interests into outcomes, is subject to at least three difficulties:
International organizations, governments and non-governmental organizations have limited resources. They cannot choose and fund all policy or programme proposals. This means that the actors who participate directly or indirectly in resource allocation must decide which proposals to drop and which to keep. They must do so according to large numbers of alternatives and often multiple goals. Typically, they must satisfy beneficiaries, different local contexts, donors, different objectives (often multiple SDG targets), and must account for constraints and interconnections with other policies. This process is tedious as it requires an overview as well as an in-depth understanding of both policy proposals and goals.
In policy contexts, decisions are often made by groups and in consultation with stakeholders. While groups and consultations allow decision-makers to understand different perspectives, they also exacerbate the difficulties linked to prioritization. Individuals and organizations operate in different contexts, may have different values and approaches, and likely have different preferences. Moreover, groups exhibit additional biases, such as groupthink, or tend to make suboptimal decisions in the presence of information asymmetries. Therefore, decision-making groups need strategies to account for the collective nature of policy decisions.
Complexity & uncertainty
Decision-making groups face incomplete information. They need strategies to identify best guesses and make decisions regardless of the state of evidence. Ideally, they integrate scientific evidence or advice in their decision-making but the question is how? Which parts of the decision require evidence? How to deal with quantitative and qualitative evidence? Lastly, decision-making groups can reduce uncertainty over time if they adequately learn from past decisions. Therefore, they need strategies to make explicit decisions, state hypotheses, document their process, and update their thinking and approach as a function of new knowledge.
Relevance for International Geneva
Teams within United Nations agencies need to make decisions at a global level which must satisfy different national contexts, different stakeholders (donors, beneficiaries), and different goals (SDGs). There is a lot of external work supporting formal UN negotiations, especially conducted by operational agencies who develop policy programmes. Except for WHO’s guideline production process, it is not clear which process these agencies follow, and which tools they use. Initial interactions with UN agencies have shown a strong interest in tools (instead of or in addition to evidence) to understand and improve their decision-making processes.
Solution: multi-criteria decision analysis for evidence-based prioritization
MCDA refers to a set of methods to account for multiple objectives and options with the goal of explicitly prioritizing the best option. All MCDA methods have four steps: (1) identify selection criteria, their weights and metrics; (2) identify options; (3) rate the performance of each option per criterion; (4) determine preferences by aggregating a score for each option and comparing results. This analysis technique has been applied for almost a century and to thousands of cases. A core contribution from operations research, MCDA’s most valuable feature may be that it can transparently account for conflicting preferences, as is often the case in policy-making.
MCDA is not only a tool. It is also a way of thinking that contributes to mindset changes. For instance, MCDA incentivises actors to acknowledge uncertainty, express confidence in their assessment, cultivates explicit reasoning and communication, and trains individuals in making hard choices in situations of resource scarcity.
Usefulness of MCDA according to the latest research
Despite difficulties in implementing MCDA, the research is clear about its value for decision-making support in policy context. It facilitates the scoring of an often vast option space on competing decision-relevant criteria. It structures the exploration of possible scenarios, provides a formatted overview, enables replicability and psychological comfort while highlighting knowledge gaps and laying the necessary groundwork to update current assumptions. As a result, stakeholder relationships become more structured and transparent, increasing trust.
MCDA’s usefulness in collective decision-making is due to the capacity to account for multidimensional problems, quantitative and qualitative data, competing interests and differing judgments. Its vast applications have proven its adaptability and employability across cultures and domains to make better choices and systematically learn from them. Compared to other popular strategies, MCDA has the strongest evidence base and large impact potential
Cohen, B., Blanco, H., Dubash, N. K., Dukkipati, S., Khosla, R., Scrieciu, S., Stewart, T., & Torres-Gunfaus, M. (2019). Multi-criteria decision analysis in policy-making for climate mitigation and development. Climate and Development, 11(3), 212–222. https://doi.org/10.1080/17565529.2018.1445612
Esmail, B. A., & Geneletti, D. (2018). Multi-criteria decision analysis for nature conservation: A review of 20 years of applications. Methods in Ecology and Evolution, 9(1), 42–53. https://doi.org/10.1111/2041-210X.12899
Kapiriri, L., & Razavi, D. (2017). How have systematic priority setting approaches influenced policy making? A synthesis of the current literature. Health Policy, 121(9), 937–946. https://doi.org/10.1016/j.healthpol.2017.07.003
Montibeller, G., & von Winterfeldt, D. (2018). Individual and Group Biases in Value and Uncertainty Judgments. In L. C. Dias, A. Morton, & J. Quigley (Eds.), Elicitation: The Science and Art of Structuring Judgement (pp. 377–392). Springer International Publishing. https://doi.org/10.1007/978-3-319-65052-4_15
Wątróbski, J., Jankowski, J., Ziemba, P., Karczmarczyk, A., & Zioło, M. (2019). Generalised framework for multi-criteria method selection. Omega, 86, 107–124. https://doi.org/10.1016/j.omega.2018.07.004
Glaize, A., Duenas, A., Martinelly, C. D., & Fagnot, I. (2019). Healthcare decision-making applications using multicriteria decision analysis: A scoping review. Journal of Multi-Criteria Decision Analysis, 26(1–2), 62–83. https://doi.org/10.1002/mcda.1659